Statistical Measures: Mean, Median, and Dispersion Techniques

This lecture covers essential statistical concepts, focusing on measures of central tendency such as the mean and median, and their sensitivity to outliers. The instructor discusses the calculation of the mean for both populations and samples, highlighting the impact of outliers on the mean's reliability. Various methods to identify and handle outliers, including quartiles and box plots, are introduced. The lecture also explains the importance of the median as a more robust measure of central tendency in the presence of outliers. Additionally, the concepts of dispersion, including range, variance, and standard deviation, are explored, emphasizing their significance in understanding data variability. The instructor provides practical examples, including the analysis of service time data, to illustrate these statistical measures in action. The session concludes with a discussion on the implications of these measures in real-world applications, particularly in engineering contexts, setting the stage for future topics in probability and statistics.